Parallel Processing in Pega – Architecture Patterns That Scale
Introduction
In enterprise-scale applications, waiting for sequential steps is a luxury you can’t afford. Whether it's meeting SLAs, orchestrating integrations, or optimizing case resolution, parallel processing is your best ally when used with preci...
execution-edge.hashnode.dev4 min read
Hi Narendra Potnuru
This Blog is great. Hope you will continue these blogs.
One Quick addition to it. Job Scheduler and Data flow are powerful combination. So instead of calling the data flow explicitly in the activity, we can simply pass the data to a real-time stream dataset which is set to listened by a real-time-dataflow.
This make sures to utilize the multi-threaded feature and performance will also be great.
For better error handling, we may use queue processor in place of real-time data flow directly.
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